Utility.h File Reference

#include <iostream>
#include <sstream>
#include <type_traits>
#include "stdlib.h"
#include "TRandom.h"
#include "TMVA/DNN/Architectures/Reference.h"
#include "TMVA/DNN/Functions.h"
#include "TMVA/DNN/Net.h"

Include dependency graph for Utility.h:

This graph shows which files directly or indirectly include this file:

Namespaces
	TMVA
	Abstract ClassifierFactory template that handles arbitrary types.
	TMVA::DNN

Functions
template<typename AMatrix , typename F >
void	TMVA::DNN::applyMatrix (AMatrix &X, F f)
	Apply functional to each element in the matrix. More...
template<typename AArchitecture >
void	TMVA::DNN::constructRandomLinearNet (TNet< AArchitecture > &net)
	Construct a random linear neural network with up to five layers. More...
template<typename AMatrix >
void	TMVA::DNN::copyMatrix (AMatrix &X, const AMatrix &Y)
	Generate a random batch as input for a neural net. More...
template<typename F , typename AFloat >
AFloat	TMVA::DNN::finiteDifference (F f, AFloat dx)
	Numerically compute the derivative of the functional f using finite differences. More...
template<typename AMatrix >
void	TMVA::DNN::identityMatrix (AMatrix &X)
	Set matrix to the identity matrix. More...
template<typename AMatrix >
auto	TMVA::DNN::maximumRelativeError (const AMatrix &X, const AMatrix &Y) -> decltype(X(0, 0))
	Compute the maximum, element-wise relative error of the matrices X and Y normalized by the element of Y. More...
template<typename AFloat >
std::string	TMVA::DNN::print_error (AFloat &e)
	Color code error. More...
template<typename AMatrix >
void	TMVA::DNN::randomBatch (AMatrix &X)
	Generate a random batch as input for a neural net. More...
template<typename AMatrix >
void	TMVA::DNN::randomMatrix (AMatrix &X)
	Fill matrix with random, Gaussian-distributed values. More...
template<typename AMatrix , typename AFloat , typename F >
AFloat	TMVA::DNN::reduce (F f, AFloat start, const AMatrix &X)
	Generate a random batch as input for a neural net. More...
template<typename AMatrix , typename AFloat , typename F >
AFloat	TMVA::DNN::reduceMean (F f, AFloat start, const AMatrix &X)
	Apply function to matrix element-wise and compute the mean of the resulting element values. More...
template<typename AFloat >
AFloat	TMVA::DNN::relativeError (const AFloat &x, const AFloat &y)
	Compute the relative error of x and y normalized by y. More...
template<>
Double_t	TMVA::DNN::relativeError (const Double_t &x, const Double_t &y)
template<>
Real_t	TMVA::DNN::relativeError (const Real_t &x, const Real_t &y)
template<typename AMatrix , typename F >
void	TMVA::DNN::zipWithMatrix (AMatrix &Z, F f, const AMatrix &X, const AMatrix &Y)
	Combine elements of two given matrices into a single matrix using the given function f. More...